An acoustic metamaterial is a material designed to control, direct, and manipulate sound waves as these might occur in gases, liquids, and solids. Acoustic metamaterials permit controlling sonic waves in the negative refraction domain. See, en.wikipedia.org/wiki/Acoustic_metamaterial, expressly incorporated herein by reference.
Control of the various forms of sound waves is mostly accomplished through the bulk modulus β, mass density ρ, and chirality. The density and bulk modulus are analogies of the electromagnetic parameters, permittivity and permeability in negative index materials. Related to this is the mechanics of wave propagation in a lattice structure. Also materials have mass, and instrinsic degrees of stiffness. Together these form a resonant system, and the mechanical (sonic) resonance may be excited by appropriate sonic frequencies (for example pulses at audio frequencies). Guenneau, Sébastien; Alexander Movchan; Gunnar Pétursson; S. Anantha Ramakrishna (2007). “Acoustic metamaterials for sound focusing and confinement”. New Journal of Physics. 9 (399): 1367-2630. Bibcode:2007NJPh.9.399G. doi:10.1088/1367-2630/9/11/399.
An acoustic cloak is a device that would make objects impervious towards sound waves. This could be used to build sound proof homes, advanced concert halls, or stealth warships. The idea of acoustic cloaking is to deviate the sounds waves around the object that has to be cloaked. But realizing it in materials has been difficult, since mechanical metamaterials are needed. Making a metamaterial for sound means identifying the acoustic analogues to permittivity and permeability in light waves. It turns out that these are the material's mass density and its elastic constant. An acoustic cloak could have many applications. Walls of the material could be built to soundproof houses or it could be used in concert halls to enhance acoustics or direct noise away from certain areas. The military may also be interested to conceal submarines from detection by sonar or to create a new class of stealth ships.
See, each of which is expressly incorporated herein by reference:    Ambati, Muralidhar, et al. “Surface resonant states and superlensing in acoustic metamaterials.” Physical Review B 75.19 (2007): 195447.    Ao, Xianyu, and C. T. Chan. “Far-field image magnification for acoustic waves using anisotropic acoustic metamaterials.” Physical Review E 77.2 (2008): 025601.    Baz, A. “The structure of an active acoustic metamaterial with tunable effective density.” New Journal of Physics 11.12 (2009): 123010.    Chen, Huanyang, and C. T. Chan. “Acoustic cloaking in three dimensions using acoustic metamaterials.” Applied physics letters 91.18 (2007): 183518.    Cheng, Ying, and Xiao Jun Liu. “Three dimensional multilayered acoustic cloak with homogeneous isotropic materials.” Applied Physics A 94.1 (2009): 25-30.    Cheng, Ying, et al. “A multilayer structured acoustic cloak with homogeneous isotropic materials.” Applied Physics Letters 92.15 (2008): 151913.    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Hu, Xinhua, et al. “Homogenization of acoustic metamaterials of Helmholtz resonators in fluid.” Physical Review B 77.17 (2008): 172301.    Huang, G. L., and C. T. Sun. “Band gaps in a multiresonator acoustic metamaterial.” Journal of Vibration and Acoustics 132.3 (2010): 031003.    Lee, Sam Hyeon, et al. “Acoustic metamaterial with negative modulus.” Journal of Physics: Condensed Matter 21.17 (2009): 175704.    Li, Jensen, and C. T. Chan. “Double-negative acoustic metamaterial.” Physical Review E 70.5 (2004): 055602.    Liang, Zixian, and Jensen Li. “Extreme acoustic metamaterial by coiling up space.” Physical review letters 108.11 (2012): 114301.    Norris, Andrew N. “Acoustic cloaking theory.” Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences. Vol. 464. No. 2097. The Royal Society, 2008.    Park, Choon Mahn, et al. “Amplification of acoustic evanescent waves using metamaterial slabs.” Physical review letters 107.19 (2011): 194301.    Pendry, J. B., and Jensen Li. “An acoustic metafluid: realizing a broadband acoustic cloak.” New Journal of Physics 10.11 (2008): 115032.    Popa, Bogdan-Ioan, and Steven A. Cummer. “Homogeneous and compact acoustic ground cloaks.” Physical Review B 83.22 (2011): 224304.    Popa, Bogdan-Ioan, Lucian Zigoneanu, and Steven A. Cummer. “Experimental acoustic ground cloak in air.” Physical review letters 106.25 (2011): 253901.    Shen, Chen, et al. “Anisotropic complementary acoustic metamaterial for canceling out aberrating layers.” Physical Review X 4.4 (2014): 041033.    Shen, Huijie, et al. “Acoustic cloak/anti-cloak device with realizable passive/active metamaterials.” Journal of Physics D: Applied Physics 45.28 (2012): 285401.    Torrent, Daniel, and José Sánchez-Dehesa. “Acoustic cloaking in two dimensions: a feasible approach.” New Journal of Physics 10.6 (2008): 063015.    Torrent, Daniel, and José Sánchez-Dehesa. “Acoustic metamaterials for new two-dimensional sonic devices.” New journal of physics 9.9 (2007): 323.    Urzhumov, Yaroslav, et al. “Acoustic cloaking transformations from attainable material properties.” New Journal of Physics 12.7 (2010): 073014.    Wang, Pai, et al. “Harnessing buckling to design tunable locally resonant acoustic metamaterials.” Physical review letters 113.1 (2014): 014301.    Xie, Yangbo, et al. “Measurement of a broadband negative index with space-coiling acoustic metamaterials.” Physical review letters 110.17 (2013): 175501.    Yang, Z., et al. “Acoustic metamaterial panels for sound attenuation in the 50-1000 Hz regime.” Applied Physics Letters 96.4 (2010): 041906.    Yang, Z., et al. “Membrane-type acoustic metamaterial with negative dynamic mass.” Physical review letters 101.20 (2008): 204301.    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Vector field microphones have been reported and used. See:    Abhayapala, Thushara D., and Darren B. Ward. “Theory and design of high order sound field microphones using spherical microphone array.” Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on. Vol. 2. IEEE, 2002.    Bertet, Stéphanie, Jérôme Daniel, and Sébastien Moreau. “3D sound field recording with higher order ambisonics-objective measurements and validation of spherical microphone.” Audio Engineering Society Convention 120. Audio Engineering Society, 2006.    De Kat, Roeland, Bas W. Van Oudheusden, and Fulvio Scarano. “Instantaneous planar pressure field determination around a square-section cylinder based on time resolved stereo-PIV.” Proceedings of the 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, Lisbon, Posrtugal, 07-10 Jul., 2008, paper No. 1259. Calouste Gulbenkian Foundation, 2008.    De Kat, Roeland, Bas W. Van Oudheusden, and Fulvio Scarano. “Instantaneous planar pressure field determination around a square-section cylinder based on time resolved stereo-PIV.”Proceedings of the 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, Lisbon, Posrtugal, 07-10 Jul., 2008, paper No. 1259. Calouste Gulbenkian Foundation, 2008.    Handzel, Amir A., and P. S. Krishnaprasad. “Biomimetic sound-source localization.” IEEE Sensors Journal 2.6 (2002): 607-616.
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Miniaturized flow sensing with high spatial and temporal resolution is crucial for numerous applications, such as high-resolution flow mapping [73], controlled microfluidic systems [74], unmanned micro aerial vehicles [75-77], boundary layer flow measurement [78], low-frequency sound source localization [79], and directional hearing aids [37]. It has important socio-economic impacts involved with defense and civilian tasks, biomedical and healthcare, energy saving and noise reduction of aircraft, natural and man-made hazard monitoring and warning, etc. [73-79, 37, 7]. Traditional flow-sensing approaches such Laser Doppler Velocimetry, Particle Image Velocimetry, and hot-wire anemometry have demonstrated significant success in certain applications. However, their applicability in a small space is often limited by their large size, high power consumption, limited bandwidth, high interaction with medium flow, and/or complex setups. There are many examples of sensory hairs in nature that sense fluctuating flow by deflecting in a direction perpendicular to their long axis due to forces applied by the surrounding medium [80-83, 2, 65]. The simple, efficient and tiny natural hair-based flow sensors provide an inspiration to address these difficulties. Miniature artificial flow sensors based on various transduction approaches have been created that are inspired by natural hairs [52, 7, 84-88]. Unfortunately, their motion relative to that of the surrounding flow is far less than that of natural hairs, significantly limiting their performance [52, 7].
Directional hearing aids have been shown to make it much easier for hearing aid users to understand speech in noise [6]. Existing directional microphone systems in hearing aids rely on two microphones to process the sound field, essentially comprising a first-order directional small-aperture array. Higher-order arrays employing more than two microphones would doubtless produce significant benefits in reducing unwanted sounds when the hearing aid is used in a noisy environment. Unfortunately, problems of microphone self-noise, sensitivity matching, phase matching, and size have made it impractical to employ more than two microphones in each hearing aid.
It is well-known that the frequency response of first order arrays (using a pair of microphones) falls in proportion to frequency as the frequency is reduced below the dominant resonant frequency of the microphones. In a second order array, the response drops with frequency squared, making it difficult to achieve directional response over the required range of frequencies. It has not been possible to overcome this fundamental limitation in sensor technology through the use of signal processing; the inherent noise in the microphones and difficulties with sensor matching comprise insurmountable performance barriers. An entirely new approach to directional sound sensing as proposed here is needed to improve hearing aid performance. It is well-known that the cause of the extreme attenuation of the frequency dependence of the first and second order response is that the response is achieved by estimating either the first of the second spatial derivative of the sound pressure. In a typical sound field, such as a plane wave, these quantities inherently become much smaller as frequency is reduced. The fiber microphone described here will circumvent the adverse frequency dependence of a first order directional array by relying on the detection of acoustic particle velocity rather than pressure. This will enable the creation of first-order directionality with inherently flat frequency response. The use of these devices in an array will enable second order directionality with the frequency dependence of a pressure-based first order array, as is currently used in hearing aids.
Many portable electronic products, such as hearing aids, require miniature directional microphones. An additional difficulty with current miniature microphones is that their reliance on capacitive sensing requires the use of a bias voltage and specialized amplifier to transduce the motion of the pressure-sensing diaphragm into an electronic signal. The present invention has the potential of avoiding all of the above difficulties by providing a directional output that is independent of frequency, without the requirement of sampling the sound at multiple spatial locations, and without the need for external power. This invention has the potential of providing a very low-cost microphone.
Digital signal processing and wireless technology in hearing aids has created a technology revolution that has greatly expanded the performance of hearing aids. While wireless technology can enable the use of microphones that are not closely located [32], improved directional microphone technology can enable substantial performance improvements in any design. Regardless of the signal processing approach used, all existing directional hearing aids rely on the detection of differences in pressure at two spatial locations to obtain a directionally-sensitive signal. Of course, as the frequency is reduced and the wavelength of sound becomes large relative to the spacing between the microphones, the difference in the detected pressures becomes small and the performance of the system suffers due to microphone noise and sensitivity and/or phase mismatch. Microphone performance limitations have placed a technology barrier on the use of directional hearing aids having better than first-order directivity.
While the difficulties of implementing higher-order pressure microphone arrays have been somewhat manageable with first-order arrays using only two microphones, the resulting directionality is quite modest and has produced much less real-world benefit to hearing aid users than hoped [60]. A number of studies have explored the reasons for this including the effects of visual cues, listener's age [57, 58, 59] and the fact that typical hearing aids are not directional enough for users to notice a benefit [31]. Studies of the effects of open fittings where the ear canal is not occluded have shown that the perception of directional benefit is strongly influenced by directionality at low frequencies [30].
The ultimate aim of flow sensing is to represent the perturbations of the medium perfectly. Hundreds of millions of years of evolution resulted in hair-based flow sensors in terrestrial arthropods that stand out among the most sensitive biological sensors known, even better than photoreceptors which can detect a single photon (10−18-10−19 J) of visible light. These tiny sensory hairs can move with a velocity close to that of the surrounding air at frequencies near their mechanical resonance, in spite of the low viscosity and low density of air. No man-made technology to date demonstrates comparable efficiency.
Predicted and measured results indicate that when fibers or hairs having a diameter measurably less than one micron are subjected to acoustic excitation, their motion can be a very reasonable approximation to that of the acoustic particle motion at frequencies spanning the audible range. For much of the audible range of frequencies resonant behavior due to reflections from the supports tends to be heavily damped so that the details of the boundary conditions do not play a significant role in determining the overall system response. Thin fibers are thus constrained to simply move with the surrounding medium. These results suggest that if the diameter or radius is chosen to be sufficiently small, incorporating a suitable transduction scheme to convert its mechanical motion into an electronic signal could lead to a sound sensor that very closely depicts the acoustic particle motion over a wide range of frequencies.
It is very common to observe fine dust particles or thin fibers such as spider silk that move about due to very subtle air currents. It is well known that at small scales, viscous forces in a fluid provide a dominant excitation force. The fluid mechanics of the interaction of thin fibers with viscous fluids can present a very challenging problem in fluid-structure interaction. This is because the presence of a thin fiber will have a pronounced effect on the flow in its immediate vicinity. While even the thinnest fibers can have a dramatic influence on the motion of a viscous fluid near the fiber, in many situations, it is reasonable to expect their motion to closely resemble that of the mean flow.
The motion of a thin fiber that is held on its two ends and subjected to oscillating flow in the direction normal to its long axis is considered. The flow is assumed to be associated with a plane traveling sound wave. The main task here is to determine if there is a set of properties (such as radius, length, material properties) that will enable the fiber's motion to constitute a reasonable approximation to the acoustic particle motion. For sound in air, fibers having a diameter that is at the sub-micron scale, exhibit motion that corresponds to that of the surrounding air over the entire audible range of frequencies.
For objects that are sufficiently small, some insight into the forces and subsequent motion can be acquired by considering the air to behave as a viscous fluid. The viscous forces in a fluid applied to a thin cylinder were perhaps first analyzed by Stokes [50]. This problem is one of the few in fluid mechanics that submits to treatment by mathematical analysis. Slender body theory for the determination of fluid forces on small solid objects has been examined at length since Stokes' time [49]. Stokes obtained series solutions for the forces and fluid motion due to a cylinder oscillating in a viscous fluid. His effort predated the existence of Bessel functions which enable the solution to be expressed in a convenient and compact form that can now be easily evaluated for a wide range of physical parameters [64].
More recent interest in nanoscale systems (either man-made or natural) has spawned renewed enthusiasm for this topic. The flow-induced motion of one or a pair of adjacent fibers held at one end has been examined by Huang et al. [26]. Numerical solutions for the motion of a collection of finite, rigid, thin fibers in a fluid due to gravity have been presented by Tornberg and Gustaysson [53]. Tornberg and Shelly examined the motion of thin fibers in a fluid that were free at each end [54]. Gotz [11] presents a detailed study of the fluid forces on a thin fiber of arbitrary shape. Shelly and Ueda [48] studied the effects of changes in the fiber shape (perhaps as it grows or stretches) on the fluid forces and the resulting motion. Bringley [4] has proposed an extension of the immersed boundary method in which the solid body is represented by a finite array of points.
The use of fibers to sense sound has proven to be a highly effective approach, having been used in nature for millions of years. There have been a number of studies of the use of thin fibers or hairs by animals to detect acoustic signals. Humphrey et al. [27] provide a model for the motion of arthropod filiform hairs extending from a substrate that follows the results provided by Stokes [50]. Bathellier et al. [2] have examined a model for the motion of a filiform hair in which it is represented by a thin rigid rod that pivots about its base. The base support is represented by a torsional dashpot and a torsional spring. The torsional dashpot at the base accounts for the absorption of energy by the sensory system.
For sufficiently long, thin hairs, there will also be substantial damping due to viscous forces in the fluid, which also provide the primary excitation force. It is well known that the maximum energy transfer (or harvesting) occurs when the impedance of the sensor matches that of the detection circuitry so one would expect optimal energy transfer at resonance and where the damping in the fluid matches that of the substrate support. Depending on the method used to achieve transduction from mechanical to electrical domains, it may be more beneficial to simply design for maximum displacement (or velocity) rather than maximum energy transfer, which can occur only at resonance when the contributions due to stiffness and inertia in the impedance cancel. Bathellier et al. [2] also make the very important observation that if one wishes to sense signals at frequencies above the resonant frequency of the hair, it is desirable that the hair be very thin and lightweight so that damping forces due to air viscosity dominate over those associated with inertia.
Mosquitoes detect nano-meter scale deflections of the sound-induced air motion using their antennae [9]. Male mosquitoes often have antennae with a large number of very fine hairs that provide significant surface area and subsequent drag force from the surrounding air. Rotations at the base of the antennae are detected by thousands of sensory cells in the Johnston's organ [28]. The transduction process used in some insects has been demonstrated to employ active amplification which was previously believed to occur only in vertebrates having tympanal ears [10, 43]. Spiders also employ remarkable sensor designs to transduce the extremely minute rotation or strain at the base of a hair into a neural signal [1].
Hairs have also been shown to enable jumping spiders to hear sound at significant distances from the source. [65].
Sound sensors composed of thin, lightweight structures have been in use since the earliest days of audio engineering. The vast majority of microphones are designed to detect pressure by sensing the deflection of a thin membrane on which the sound pressure acts. The ribbon microphone consists of a thin, narrow conducting ribbon that is designed to respond to the spatial gradient of the sound pressure due to the pressure difference across its two opposing faces [29, 44, 45]. The ribbon is placed in a magnetic field and the open circuit voltage across the ribbon is proportional to the ribbon's velocity [45]. The electrical output is roughly proportional to the acoustic velocity which, in a plane sound wave, is also proportional to the sound pressure.
The present approach could be viewed as an extension of the ribbon microphone design where the ribbon is replaced by a fiber. The ribbon microphone normally uses electrodynamic transduction. It should be noted that unlike the fiber microphone described here, the essential operating principle of a ribbon microphone is not dependent on fluid viscosity; the ribbon is considered to be driven by pressure gradients, even in an inviscid fluid medium.
A number of engineered devices have been fabricated over the past decade in an attempt to approach the flow sensing capabilities of insect hairs. A comprehensive review of engineered flow sensors based on hairs is provided in [52]. The overall approach in these designs is to create a light-weight, rigid rod with sensing incorporated at the rotational support at the base. The flow-induced motion of MEMS flow sensors has been found to be more than two orders of magnitude less than that of cricket cercal hairs [7].
Because the present technology can measure motion of thin structures that are driven by viscosity, it is also possible to measure the acoustic particle velocity by detecting the heat flow around a fine wire that is heated by an electric current. This principle has been employed in a successful commercial sound sensor, the Microflown [66].
Sound velocity vector sensors have also been employed in liquids to detect the direction of propagation of underwater sound [67]. As with the ribbon microphone, these devices generally are intended to respond to pressure gradients or differences across their exterior rather than on viscous forces; analysis of their motion does not depend on the fluid viscosity.